Effect of Die Dimensions on Extrusion Processing Parameters and Properties of DDGS-Based Aquaculture Feeds

Transcription

1 Iowa State University From the SelectedWorks of Kurt A. Rosentrater June, 2007 Effect of Die Dimensions on Extrusion Processing Parameters and Properties of DDGS-Based Aquaculture Feeds Nehru Chevanan, South Dakota State University Kasiviswanathan Muthukumarappan, South Dakota State University Kurt A. Rosentrater, United States Department of Agriculture James L. Julson, South Dakota State University Available at:

2 Effect of Die Dimensions on Extrusion Processing Parameters and Properties of DDGS-Based Aquaculture Feeds Nehru Chevanan, 1 Kasiviswanathan Muthukumarappan, 2,3 Kurt A. Rosentrater, 4 and James L. Julson 5 ABSTRACT Cereal Chem. 84(4): The goal of this study was to investigate the effect of die nozzle dimensions, barrel temperature profile, and moisture content on DDGSbased extrudate properties and extruder processing parameters. An ingredient blend containing 40% distillers dried grains with solubles (DDGS), along with soy flour, corn flour, fish meal, whey, mineral and vitamin mix, with a net protein content adjusted to 28% was extruded in a single-screw laboratory extruder using seven different die nozzles. Increasing moisture content of the ingredient mix from 15 to 25% resulted in a 2.0, 16.0, 16.3, 22.9, 18.5, 32.5, and 63.7% decrease, respectively, in bulk density, water-solubility index, sinking velocity, L*, b*, mass flow rate, and absolute pressure, as well as 11.6, 16.2, and 7% increases, respectively, in pellet durability, water-absorption index, and a*. Increasing the temperature from 100 to 140 C resulted in 17.0, 5.9, 35.4, 50.6, 28.8, 33.9, and 33.9% decreases, respectively, in unit density, pellet durability, sinking velocity, absolute pressure, specific mechanical energy, torque, and apparent viscosity, but a 49.1 and 16.9% increase, respectively, in dough temperature and water-absorption index. Increasing the L/D ratio of the die nozzle resulted in an increase in bulk density, L*, a*, and torque, but a decrease in unit density, pellet durability, water-absorption index, sinking velocity, b*, mass flow rate, dough temperature, and apparent viscosity. As demonstrated in this study, the selection of an appropriate die geometry, in addition to the selection of suitable temperature and moisture content levels, are critical for producing DDGS-based extrudates with optimum properties. Distillers dried grains with solubles (DDGS) typically contain high amounts of protein (23 29%) and low levels of starch (1 2%) and are thus a possible alternative protein source for aquaculture feeds (Chin et al 1989; Lee et al 1991; Wu et al 1994, 1996). Depending on the species, aquaculture feeds generally require protein contents of 26 50% (Lovell 1989). Consequently, these formulated feeds can contain high quantities of both protein and starch. Floatability of the extrudates is an important quality parameter for aquaculture feeds (Bandyobadhyay and Ranjan 2001; Rolfe et al 2001). The unit density of extrudates, which affects the floatability, depends on the extent of expansion obtained during extrusion cooking. Expansion can be controlled by changing the type and nature of ingredients used, and by changing the processing conditions in the extruder. In the extrusion industry, starch-based ingredients are often used to obtain puffed products, while proteinbased ingredients are often used to obtain texturized products (Kokini et al 1992). During extrusion processing of starch-based products, the extent of gelatinization occurring inside the barrel plays an important role in determining final extrudate properties. Depending on the extent of gelatinization, the ingredient mix is turned into an elastic melt inside the barrel (Case et al 1992; Sokhey et al 1994; Ibanoglu et al 1996; Ilo et al 1996; Lin et al 2000). When the elastic melt exits through the die, expansion occurs due to the flashing of water vapor, which occurs due to the sudden drop in pressure (Alves et al 1999; Lam and Flores 2003). During the extrusion processing of protein-based products, on the other hand, the ingredient mix becomes more of a plastic melt inside the barrel. The protein can be denatured due to the heat, which results in modifications in the peptide bonds and amino acid chains. When the material exits through the die, it is in a plastic, homogenous state, and a more porous, fibrous textured product generally results, often due to the voids formed by the steam generated during 1 Graduate research assistant, South Dakota State University, Brookings, SD Professor, South Dakota State University, Brookings, SD Corresponding author. Phone: Fax: address: muthukum@sdstate.edu 4 Bioprocess Engineer, North Central Agricultural Research Laboratory, USDA, ARS, Brookings, SD Mention of a trade name, propriety product or specific equipment does not constitute a guarantee or warranty by the United States Department of Agriculture and does not imply approval of a product to the exclusion of others that may be suitable. 5 Professor, South Dakota State University, Brookings, SD doi: / CCHEM AACC International, Inc. sudden pressure drop (Gwiazda et al 1987; Singh et al 1991; Sandra and Jose 1993). Operation of extruders depends on many factors, including the pressure developed inside the die, slip at the barrel wall, and the degree to which the screw is filled. The combination of these variables, along with the type and composition of raw ingredients used, will affect operational capabilities (Mercier et al 1989). The extruder die plays an important role in affecting the processing conditions as well. For circular dies, nozzle dimensions (i.e., nozzle diameter and length) will affect process conditions and performance (Chinnaswamy et al 1987). The flow of dough inside a circular shaped die (Q) is directly proportional to the pressure developed inside the die ( P), and inversely proportional to the apparent viscosity (μ d ) of the dough inside the die. This can be mathematically expressed as where K is a proportionality factor, which, for a circular die with a nozzle radius of R and nozzle length of L, can be expressed as (Sokhey et al 1997) The rheological and thermodynamic processes occurring inside the die during forming and stretching have decisive effects on the final quality of extruded products (Mercier et al 1989). Apparent viscosity is the most important rheological property that affects final product properties. During extrusion of biologically based feed materials, ingredients often transform into a pseudoplastic melt. And the moisture content of the ingredients, as well as cooking temperature, often significantly affect the apparent viscosity and thus the final extrudate properties (Harper 1981; Rosentrater et al 2005; Shukla et al 2005). Therefore, the objective of this study was to investigate the effect of the die nozzle dimensions, barrel temperature profile, and moisture content on the DDGS-based extrudate properties, and extruder processing parameters. MATERIALS AND METHODS Sample Preparation An ingredient blend containing 40% DDGS, along with appropriate quantities of soy flour, corn flour, Menhaden fish meal, whey, vitamin and mineral mix, with the net protein adjusted to 28% was prepared following Chevanan et al (2005a,b). DDGS was provided by Dakota Ethanol LLC (Wentworth, SD) and was (1) (2) Vol. 84, No. 4,

3 ground to a particle size of 100 μm using a laboratory grinder (S500 disc mill, Genmills, Clifton, NJ). Corn flour was provided by Cargill Dry Ingredients (Paris, IL), and soy flour was provided by Cargill Soy Protein Solutions (Cedar Rapids, IA). The ingredients were mixed in a laboratory-scale mixer (N50 mixer, Hobart Corporation, Troy, OH) for 10 min, and then stored overnight at refrigerated conditions (10 ± 1 C) for moisture stabilization. The moisture content of the ingredient mix was adjusted by adding required quantities of water during mixing. Experimental Design The extrusion studies were conducted using a single-screw extruder (Brabender Plasti-Corder, model PL 2000, South Hackensack, NJ), which had a barrel of mm, with a length to diameter ratio of 20:1. The die assembly had an internal conical section and a length of mm. A screw with a uniform pitch of 9.05 mm was used in the experiments. The screw had variable flute depth, with the depth at the feed portion of 9.05 mm, and near the die of 3.81 mm. The compression ratio achieved inside the barrel was 3:1. The speed of the screw and the temperature inside the barrel were controlled by a computer control system. The extruder barrel s band heaters allowed the temperature of the feed zone, transition zone in the barrel, and the die section to be controlled. Compressed air cooling was provided in the barrel section as well, but the die section was not cooled. The extruder had a 7.5 HP motor, and the computer system could control the speed of the screw at rpm (0 22 rad/sec). Experiments were conducted with a full-factorial design using three levels of moisture content (MC) (15, 20, and 25%, wb); three levels of temperature gradient in the barrel ( C, , and C) hereafter referred to as temperatures of 100, 120, and 140 C, respectively; and seven levels of die geometry with various nozzle length to diameter ratios. The dimensions of the seven different dies used in the experiments are given in Table I. Measurement of Extrudate Properties Unit density (UD). Extrudates were cut with a razor blade into 20-mm lengths. UD was determined as the ratio of mass to the calculated volume of each piece by assuming cylindrical shapes for each extrudate according to Jamin and Flores (1998). Bulk density (BD) was measured using a standard bushel tester (Seedburo Equipment Co., Chicago, IL) following the method prescribed by the USDA (1999). Pellet durability (PD) was determined following ASAE standard method S269.4 DEC01 (1996); 200 g of the extrudates was tumbled inside a pellet durabilty tester (Seedburo) for 10 min and then hand-sieved through a No. 6 screen. PD was calculated as PD = (Mass of pellet after tumbling/mass of pellet before tumbling) 100 Water absorption index (WAI) was determined according to Jones et al (2000). To determine WAI, 2.5 g of finely ground sample was suspended in 30 ml of distilled water at 30 C in a 50-mL tarred centrifuge tube. The content was stirred intermittently over Die No. TABLE I Dimensions of Dies Used in Study Diameter of Nozzle (mm) Length of Nozzle (mm) L/D Ratio (3) 30 min and then centrifuged at 3,000 g for 10 min. The supernatant water was transferred into tarred aluminum dishes. The mass of the remaining gel was weighed, and WAI was calculated as the ratio of gel mass to the sample mass. Water-solubility index (WSI) was determined as the water-soluble fraction in the supernatant, expressed as percent of dry sample (Jones et al 2000). The WSI was determined from the amount of dried solids recovered by evaporating the resulting supernatant in an oven at 135 C for 2 hr; it was determined as the mass of solids in the extract to the original sample mass (%). Sinking velocity (SV) was measured following the method adopted by Himadri et al (1993). SV was measured by recording the time taken for an extrudate 20 mm long to travel from the surface of water to a depth of 425 mm in a 2,000-mL graduated cylinder. Color of the extrudates was determined using a spectrophotometer (portable model CM 2500d, Minolta Corporation, Ramsey, NJ) using the L-a-b opposable color space, where L* quantifies the brightness, a* quantifies redness/greenness, and b* quantifies yellowness/blueness. Extrusion Processing Parameters The temperature of the ingredient melt at the end of the barrel (TB) was measured with a Type J thermocouple with a range of C. The absolute pressure (P) inside the die was recorded with pressure transducer that had a range of MP. The temperature of the melt in the die (TD) was recorded with a thermocouple that was integral to the pressure transducer. The net torque ( ) was measured with a torque transducer that had a range of 0 40,000 m-g. During experimentation, the extrudate samples were collected for 30-sec intervals, and the mass flow rate (MFR) was then calculated (g/min). Based on the torque and the mass flow rate data, the various processing variables were then determined. Specific mechanical energy (SME) (J/g) was calculated according to Harper (1981) and Martelli (1983) as (4) where Ω is the net torque exerted on the extruder drive (N-m), ω is the angular velocity of the screw (rad/sec), and m feed is the mass flow rate (g/min). Apparent viscosity (η) of the dough in the extruder (Pa-sec) was calculated by approximating the barrel and screw as a concentric cylinder viscometer, and then incorporating corrections for tapered screw geometry (Rogers 1970; Lo and Moreira 1996; Konkoly 1997; Lam and Flores 2003; Rosentrater et al 2005). The apparent viscosity was determined as the ratio of shear stress (τ s ) at screw (N/m 2 ) to the shear rate (γ s ) at the screw (1/sec) calculated from Equations 5 and 6 where r corr is the radius correction due to frustum value (5) (6a) (6b) where r eff is the effective radius including the screw root radius and half of flight height (m), L is the screw length in the axial direction (m), C ss is a correction factor for shear stress ( for the screw used), γ s is the shear rate at the screw (1/sec), r b is the barrel radius (m), and C sr is the correction factor for shear rate (6.31 for the screw used). Statistical Analysis The measurements were completed in triplicate for all extrudate properties and extrusion processing parameters, except for pellet durability, which was measured in duplicate. The data were 390 CEREAL CHEMISTRY

4 then analyzed with Proc GLM to determine the main and interaction effects and LSD using α = 0.05 for comparison, with SAS v.8 software (SAS Institute, Cary, NC). To determine the effect of nozzle length (L), nozzle diameter (D), and length to diameter ratio (L/D) on individual response variables, multiple linear regression analysis was conducted with linear quadratic models Response = I 1 + a 1 * D + a 2 * MC + a 3 * T + a 4 * D * T + a 5 * D * (7) MC + a 6 * T * MC + a 7 * D 2 + a 8 MC 2 + a 9 T 2 Response = I 2 + b 1 * L + b 2 * MC + b 3 * T + b 4 * L * T + b 5 * L * MC + b 6 * T * MC + b 7 * L 2 + b 8 MC 2 + b 9 T 2 Response = I 3 + c 1 * (L/D) + c 2 * MC + c 3 * T + c 4 * (L/D) * T + c 5 * (L/D) * MC + c 6 * T * MC + c 7 * (L/D) 2 + c 8 MC 2 + c 9 T 2 The Proc Reg procedure in SAS was used to determine the coefficients for each of the terms, and only statistically significant terms were included in the final model using a step-wise selection method. In Equations 7, 8, and 9, I 1, I 2, and I 3 are the intercept values; a 1 a 9, b 1 b 9, and c 1 c 9 are the regression coefficients for respective terms; D, L, L/D, MC, and T represent the diameter (mm), length (mm), length-to-diameter ratio of the die nozzle (-), moisture content (%, wb) of the blend, and temperature ( C), respectively. (8) (9) RESULTS AND DISCUSSION Changing the levels of temperature, moisture content, and die dimensions were each found to have significant effects on all the extrudate properties studied, except for UD, where the effect of moisture content was not significant (Table II). Temperature, moisture content, and die dimensions also significantly affected all extrusion processing parameters as well (Table III). Additionally, the interaction effects were also significant (P < 0.05) for all the extrudate properties, except for die*moisture content and die* moisture content*temperature for UD, and temperature*moisture content for WSI. The interaction effect of temperature, moisture content, and die dimensions were also significant for all the extrusion processing variables studied. With regression, it was determined that L/D, moisture content, and temperature (using Equation 9) predicted all extrudate properties and the extrusion processing parameters with high R 2 values compared with L or D alone as the primary geometric parameters (Equations 7 and 8). Hence, regression modeling using L/D as the die geometry parameter was pursued for all subsequent analysis. Extrudate Properties Unit density (UD), which affects floatability of extrudates, is a very important quality parameter for aquaculture feed materials. TABLE II Main Treatment Effects on the Physical Properties of Extrudates a Unit Bulk Pellet Water Water Sinking Density Density Durability Absorption Solubility Velocity Color Parameter (g/cm 3 ) (g/cm 3 ) (%) Index Index (%) (m/sec) L* a* b* Temp profile ( C) a 0.45b 95.75a 2.63c 17.71a 0.10a 40.92b 4.30c 13.98ab b 0.45a 94.61b 2.90b 17.70a 0.09b 41.39a 4.37b 14.06a c 0.42c 87.19c 3.13a 16.95a 0.07c 39.65c 4.51a 13.91b Moisture content (%) a 0.44a 86.95c 2.73c 18.33a 0.09a 44.41a 4.26c 15.12a a 0.44b 92.40b 2.88b 17.57b 0.08b 42.39b 4.32b 14.33b a 0.44b 97.04a 3.01a 16.66c 0.08c 36.13c 4.56a 12.76c L/D (-) D (mm) ab 0.43d 94.55c 2.99a 17.03c 0.08d 39.28c 4.35cd 13.36e b 0.48a 85.06e 2.85b 17.45b 0.12a 41.30b 4.38bcd 14.62a c 0.45b 87.17d 2.96a 16.44d 0.10b 40.78b 4.46b 14.13b ab 0.43d 95.06b 2.86b 17.61b 0.07e 41.27b 4.15e 13.71d ab 0.42f 95.21b 2.95a 18.30a 0.08c 41.32b 4.31d 13.90c a 0.42e 97.99a 2.84b 17.34bc 0.07f 38.09d 4.67a 13.76cd a 0.44c 94.23c 2.78c 17.99a 0.08d 42.13a 4.41bc 14.17b a Values with the same letter in a column for a given factor are not significantly different (P < 0.05). Parameter TABLE III Main Treatment Effects on Extrusion Processing Parameters a Mass Flow Rate (g/min) Torque (N-m) SME (J/g) Apparent Viscosity (Pa-sec) Absolute Pressure (MPa) Dough Temp (Barrel) ( C) Dough Temp (Die) ( C) Temp profile ( C) c 74.04a a a 10.91a c c b 62.89b b b 7.71b b b a 55.24c c c 5.38c a a Moisture content (%) a 62.07b b b 12.82a a c b 89.12a a a 8.02b b b c 41.03c b c 4.65c c a L/D (-) D (mm) g 59.05d c d 4.01f b a a 54.67e e e 3.94f d e b 56.41de e de 5.05e ab c e 65.06c c c 9.32c a b f 57.26de d de 7.91d c e c 80.06a a a 11.88b ab d d 74.47b b b 13.87a a d a Values with the same letter in a column for a given factor are not significantly different (P < 0.05). Vol. 84, No. 4,

5 Increasing the moisture content of the ingredient mix had no significant effect (P > 0.05) on the UD of the extrudates. However, increasing the temperature from 100 to 140 C resulted in a significant decrease (17%) in UD of extrudates. Many researchers have observed that temperature has an inverse relationship with the apparent viscosity of the ingredient melt inside the barrel and die (Harper et al 1981; Bhattacharya and Hanna 1986), and that higher temperatures typically result in lower apparent viscosity of the melt. When the ingredient melt (at lower viscosities) exits through the die, extrudates tend to expand more and, thus, have reduced UD. Regression analysis for UD resulted in an R 2 value 0.65 using L/D as the geometric parameter. Model equation 10 predicts the UD of extrudates with L/D, MC, and T (Table V). The negative value for the term containing L/D, within the bounds of the experiment, indicated that there was a general trend of decrease in UD as the L/D ratio was increased. Bulk density (BD) is another key property, as it influences storage space required at the processing plant, during shipping, and at animal production facilities. BD depends on the size, shape, and the extent of expansion during extrusion. Increasing temperature had a significant effect on the BD (P < 0.05). The lowest BD (0.319 g/cm 3 ) was recorded at a T of 140 C, MC of 25%, and L/D of The highest BD (0.509 g/cm 3 ) was recorded at a T of 120 C, MC of 20%, and L/D of 3.33 (Table IV). Changing the MC of ingredient mix also had a significant effect on the BD (P < 0.05): increasing MC from 15 to 25% resulted in a 2% decrease in BD. The R 2 value of the linear quadratic model with L/D as the geometric parameter was Model equation 11 predicts BD using L/D, MC, and T (Table V). A positive coefficient for the L/D and (L/D) 2 terms in the model indicate that there was general increasing trend in BD as the L/D ratio was increased. Pellet durability (PD), which is an important quality parameter of feed materials (Rosentrater et al 2005), can indirectly assess the mechanical strength of extrudates. Increasing T resulted in a significant decrease in the PD (P < 0.05). The PD at T of 100 C was 9.8% higher compared with the PD at T 140 C (Table II). Changing the MC of the ingredient mix also had a significant effect on the PD of the extrudates; and PD at 25% MC was 11.9% higher compared with the PD at 15% MC. At higher MC, the temperature of dough at the die was significantly higher as well (Table III). The mechanical strength of extrudates depends on the extent of heat treatment and the relative degree of starch gelatinization that occurs during processing (Colonna et al 1989). Increasing the MC and T synergistically resulted in a higher extent of heat treatment and gelatinization, which resulted in higher PD. The R 2 value of the linear quadratic model using L/D as the geometric parameter was Model equation 12 predicts PD with L/D, MC, and T (Table V). A negative coefficient for the L/D, L/D*MC, and (L/D) 2 terms in the model indicated that there was, in general, a decreasing trend in PD as the L/D ratio was increased. The higher PD at lower T is indicated by the negative coefficient of ( * MC) for the T term, while the higher PD at higher MC is summarized by the positive coefficient of (0.04*T 2.31) for the MC term. Water-absorption index (WAI) is related to the extent of starch that has maintained integrity during extrusion processing, and to the molecular breakdown of starch and protein components. WAI is also indirectly related to water-holding capacity, which thus affects product storage stability. T had a significant effect on the WAI (P < 0.05); the WAI was 16.9% higher at a T of 140 C compared with the WAI at a T of 100 C (Table II). A similar trend was observed by Anderson et al (1969) with extruded corn grits. 392 CEREAL CHEMISTRY

6 Changing the MC of the ingredient mix also had a significant effect on the WAI (P < 0.05). Increasing the MC from 15 to 25% resulted in a 16.2% increase in the WAI. Anderson (1982) observed that higher temperatures and higher moisture contents could result in greater starch breakdown and thus increased formation of an expansible matrix, resulting in higher water-holding capacity, which could lead to an increased extrudate WAI. In this study also, higher T and higher MC resulted in higher WAI of the extrudates. The R 2 value for the linear quadratic model with L/D as the geometric parameter was Regression equation 13 predicts WAI with L/D, MC, and T (Table V). The negative coefficient for the L/D term in the model indicated that there was a general decreasing trend in WAI as L/D ratio increased. Higher WAI at higher MC and higher T are indicated by the positive coefficients for MC and T terms in the model. Water-solubility index (WSI) is directly related to the extent of starch gelatinization that occurs inside the extruder (Harper 1981). Generally, WSI increases as the temperature increases, due to starch depolymerization, which leads to reduced length of amylose and amylopectin chains (Anderson et al 1982). In our experiments using DDGS, changing T did not result in significant changes in the WSI of the extrudates. But changing MC did have a significant effect. William et al (1977) observed drier conditions of the ingredients affected the extent of dextrinization of starch, which resulted in higher extrudate WSI. Similarly, in this study the WSI at 15% MC was 16.0% higher compared with the WSI at 25% MC. The R 2 value with L/D as the geometric parameter in the linear quadratic model was Model equation 14 predicts WSI with L/D, MC, and T (Table V). The very low R 2 value for the resulting model indicated that WSI may be controlled by various other factors such as residence time, extent of shear, etc., in addition to die dimensions, MC, and T during processing. Sinking velocity (SV) depends on the extent of expansion and, thus, the biochemical changes occurring inside the barrel. Extrudate expansion affects density of extrudates as well. Moreover, the extent of biochemical changes affect the water-absorption capacity and structural integrity of extrudates, which also affect the SV. The SV of the extrudates significantly (P < 0.05) decreased (35.4%) at higher T, indicating that the extrudates had a decreased UD and better buoyancy. Even though changing the MC of the ingredient mix had no significant effect on the UD of the extrudates, the SV of the extrudates obtained at 25% MC was significantly lower (16.3%) compared with the extrudates at 15% MC (Table II). The R 2 value using L/D as the geometric parameter in the linear quadratic model was Model equation 15 predicts SV with L/D, MC, and T (Table V). The negative value for terms containing L/D, within experimental boundaries, indicated that there was, in general, a decreasing trend in SV as the L/D ratio increased. Lower SV at higher MC and higher T is indicated by the negative coefficient for the MC and T terms in the model equation. Vol. 84, No. 4,

7 Color change in extrusion processing is mostly due to Maillard reactions (Mercier et al 1989). In fact, significant losses of lysine (an important amino acid required for fish growth) during extrusion processing (Bjorck and Asp 1983) have been observed due to Maillard reactions. Extrudates obtained at a T of 140 C had lower brightness (L*) and yellowness (b*) values, but had a higher redness (a*) value (Table II). A similar trend was observed by Shukla et al (2005) during extrusion experiments with raw materials that also contained DDGS. This may have been due to Maillard reactions, which resulted in the browning of extrudates at higher temperatures. Increasing the MC from 15 to 25% resulted in a 22.9 and 18.5% decrease, respectively, in brightness and yellowness, but a 7.0% increase in the redness of the extrudates. In general, extrudates obtained with higher MC had lower brightness and yellowness values and higher redness values. This might have been due to the higher resulting temperature of the ingredient melt at the die (Table III), which may have contributed to the browning. Changing the die dimensions also had a significant effect on resulting color values: model equations 16, 17, and 18 (Table V) predict the color of the extrudates with L/D, MC, and T (R 2 for L* = 0.70, R 2 for a* = 0.29, and R 2 for b* = 0.76). Within the scope of the experiment, the positive value for the term containing L/D in the model indicated that there was a general increasing trend in L* as the L/D ratio was increased. Similarly, a positive value for the term containing L/D in the model indicated that there was an increase in a* as the L/D ratio was increased. On the other hand, the negative coefficient for the L/D term in the model for b* indicated that there was a decrease in b* as the L/D ratio was increased. Extrusion Processing Parameters Mass flow rate (MFR) in a single-screw extruder depends on the drag flow developed by screw rotation and the pressure flow developed due to the restriction of the die (Mercier et al 1989). In this study, increasing T from 100 to 140 C resulted in a significant increase (3.9%) in the MFR (P < 0.05). On the other hand, increasing the MC from 15 to 25% resulted in a 32.5% decrease in the MFR. The R 2 value using L/D as the geometric parameter in the linear quadratic model was Regression equation 19 predicts MFR using L/D, T, and MC (Table V). A negative coefficient for L/D in the model indicated that there was a decreasing trend in MFR as the L/D ratio was increased. The decrease in MFR with higher MC is explained by the coefficient ( * MC) for MC term in the model. The higher MFR at higher T can be explained by the positive coefficient for T in the resulting model. Dough Temperature The temperature development inside the barrel depends on thermal gradients, thermal conductivity, thermal diffusivity, degree of mixing, velocity of flow, etc., and ultimately affects the extrusion process as well as the resulting extrudate properties. Increasing T from 100 to 140 C resulted in a 23.60% increase in TB, which compared with a 49.1% increase in TD. In the extruder used, the die section did not have a compressed air cooling system, which contributed to the increase in TD. The pressure and shear developed inside the die may also have contributed to the higher TD. Increasing MC of the ingredient mix resulted in a significant (P < 0.05) decrease in TB, while the reverse was observed for TD (Table III). The R 2 value of the linear quadratic model with L/D as the geometric parameter in the TB prediction model was The R 2 value to predict TD was The resulting TB prediction equation 20 uses L/D, MC, and T (Table V). The negative value for the L/D terms indicated that there was, in general, a decreasing trend in TB as the L/D increased. A negative coefficient for MC in the model indicated that the TB decreased as the MC was increased, whereas a positive coefficient for the T term indicated that the TB increased as T increased. Regression equation 21 predicts TD with L/D, MC, and T (Table V). A negative coefficient for the L/D term in the model indicated that there was a general decreasing trend in TD as the L/D ratio was increased. On the other hand, a positive coefficient for the MC and T terms in the model indicated that there were general increasing trends in TD as the MC and T were increased. In our experiment, we observed that increasing the temperature profile in the barrel resulted in increased TD and TB (Table III) leading to a reduction in UD, BD, PD, SV, L*, and an increase in WAI and a* of the extrudates (Table II). However, increasing the moisture content of the ingredient mix resulted in reduced TD but increased TB of the molten dough. Absolute Pressure (P) The pressure developed inside the die depends on various parameters such as rheological properties of the ingredient blend and pumping characteristics, in addition to the die dimensions used in the extruder. The biochemical conversions occurring inside the barrel depend on the extent of pressure developed inside the extruder, in addition to the extent of thermal and mechanical energy available for chemical reactions, and ultimately affects the extrudate properties. Increasing the T resulted in a significant decrease in the P developed in the die (P < 0.05). In fact, increasing T from 100 to 140 C resulted in a 50.6% decrease. Moreover, at TABLE V Regression Models for Extrudate Properties and Extrusion Processing Parameters Using Moisture Content (MC), Barrel Temperature (T), and Length-to-Diameter Ratio of Die (L/D) a Eq Property a Regression Model R 2 SE CV (%) 10 UD * (L/D) * MC * T * (L/D) * MC BD * (L/D) * MC * T * (L/D) MC PD * (L/D) 2.31 * MC 1.11 * T 0.33 * (L/D) * MC * T * MC 0.54 * (L/D) WAI * (L/D) * MC * T WSI * (L/D) 0.25 * MC * T * (L/D) * T * (L/D) * MC * T * MC SV * (L/D) * MC * T * (L/D) L* * (L/D) * MC 0.03 * T 0.09 * (L/D) * MC 0.09 * (MC) a* * (L/D) 0.03 * MC * T * (L/D) * T * (L/D) * MC b* * (L/D) 0.67 * MC 0.07 * T * T * MC MFR * (L/D) * MC * T 0.60 * MC TB * (L/D) * MC * T 0.04 * (L/D) * T * (L/D) TD * (L/D) * MC * T P * (L/D) 1.27 * MC 14.0 * T 0.03 * (L/D) * MC+0.09 * T * MC 3.0 * (L/D) SME * (L/D) * MC 3.16 * T 3.03 * (L/D) * MC Ω * (L/D) * MC 0.47 * T 1.53 * MC η * (L/D) * MC 18.8*T 2.2 * (L/D) * T 15.3*(L/D) * MC 26.5 * (L/D) * MC a UD, unit density; BD, bulk density; PD, pellet durability; WAI, water-soluble index; WSI, water-soluble index; SV, sinking velocity; L*, brightness, a*, redness, b*, yellowness; MFR, mass flow rate; TB, temperature of dough at the barrel; TD, temperature of dough at die; P, pressure developed in the die; SME, specific mechanical energy; Ω, torque; η, viscosity of dough. 394 CEREAL CHEMISTRY

8 higher T, the apparent viscosity of the ingredient melt decreased (Table III). Thus the ingredient melt at lower viscosity might have resulted in decreased P inside the die. Lam and Flores (2003) observed a similar trend during extrusion of fish feed. Increasing the MC of the ingredient mix also had a significant effect on the P developed in the die. The P at 15% MC was 63.7% higher compared with the P at 25% MC. The R 2 value using L/D as the geometric parameter in the linear quadratic model was Model equation 22 predicts P with L/D, MC, and T (Table V). Within the bounds of the study, the coefficient for (L/D) 2 in the model was significant, indicating that P had a nonlinear relationship with L/D. The reduced P inside the die at higher T is indicated by the negative value for the terms containing T in the model. Increasing the temperature profile in the barrel as well as increasing the moisture content of the ingredient blend resulted in reduced P (Table III) leading to decreasing trends in UD, BD, PD, SV, L*, and increasing trends in WAI and a* (Table II). Specific Mechanical Energy (SME) In extrusion processing, the amount of biochemical reactions occurring inside the barrel depends on the thermal and mechanical energy available. To induce optimum conversion of the ingredients to obtain extrudates of high quality, appropriate combinations of shear and thermal energy are very important. The amount of Vol. 84, No. 4,

9 mechanical energy applied to the ingredient mix is measured in terms of SME. SME is the net amount of energy utilized by the extruder to produce unit mass flow rate of the material. In singlescrew extrusion, it is very difficult to control the SME because the material is transported by friction between the screw and barrel surfaces and the material. At higher T, SME decreased; increasing T from 100 to 140 C resulted in a 28.8% decrease in the SME. The reduced SME consumption at higher temperature profile in the barrel resulted in decreasing trends in UD, BD, PD, SV, L*, and increasing trends in WAI and a* value. The MC also had significant effect. The highest SME (653.6 J/g) was observed at 20% MC, while the lowest SME (184.6 J/g) was observed at 15 and 25% MC (Table VI). As expected, die dimensions also had a significant effect. The R 2 value with L/D as the geometric parameter in the linear quadratic model was Model equation 23 predicts SME with L/D, MC, and T (Table V). The (L/D) 2 term in the model indicated that there was a nonlinear trend between SME consumption and L/D ratio. A negative coefficient for T in the model indicated that there was a decrease in SME as T was increased. MC also exhibited a nonlinear relationship with SME, as indicated by the MC 2 term in the model. Torque (Ω) In general, most food and feed materials exhibit pseudoplastic behavior. As the screw speed increases, viscosity decreases, which affects the torque requirement. Reduced viscosity at higher shear rates affects the mass flow rate as well. Mass flow rate also affects the torque requirement. Hence, Ω is an important parameter in extrusion processing, and ultimately affects the quality of extrudate properties. Increasing T resulted in a decrease (P < 0.05) in the Ω required to operate the extruder (Table III). In fact, increasing T from 100 to 140 C resulted in a 33.9% decrease in Ω. This behavior occurred, at least in part, because increasing T resulted in a reduced apparent viscosity (η) of the dough, which thus required less torque to rotate the screw. The decreased torque requirement at higher temperature profile in the barrel resulted in reduced UD, BD, PD, SV, L*, and increased WAI and a* values (Table III). Changing the MC also had a significant effect on the Ω required to operate the extruder. Maximum Ω was required at 20% MC, and increasing or decreasing the moisture content from 20% resulted in reduced Ω. Changing the die dimensions also had a significant effect on Ω. The R 2 value with L/D as the geometric parameter in the linear quadratic model was Model equation 24 predicts Ω with L/D, MC, and T (Table V). A positive coefficient for the L/D term in the model indicated that there was, in general, an increasing trend in Ω requirement as L/D increased. A negative coefficient for T in the model indicated that the Ω requirement decreased as the temperature was increased. Apparent Viscosity (η) Viscosity development inside the barrel depends on ingredient composition, constituent molecular weights, processing temperatures, pressures developed, and thermomechanical history, and affects the final product properties (Gagos and Bhakuni 1992). Apparent viscosity can reveal several of these parameters and thus is often used to monitor product quality online. Increasing T from 100 to 140 C resulted in a 33.9% decrease in the η inside the barrel. Due to this decreased η, there was a decreasing trend in extrudate properties such as UD, BD, PD, SV, and an increasing trend in WAI and a* value was observed (Table II). As expected, changing the MC of the ingredient mix also had a significant effect on η. Maximum η was observed at 20% MC. Changing the die dimensions had significant effect on η as well. The R 2 value to predict η with L/D was Model equation 25 predicts η using L/D, MC, and T (Table V). The negative coefficient for the T term in the model indicated that there was a decrease in apparent viscosity as T increased. The (L/D) 2 and (MC) 2 terms in the model were also significant, indicating that the L/D of the die and MC had a nonlinear relationship with η of the ingredient melt inside the barrel. Correlation Analysis After examining individual treatment effects, as well as treatment combination effects, the multivariate data were subjected to correlation analysis to further examine relationships between the variables. The Pearson correlation coefficient r provides the strength of linear relationship between two variables (Rao 1997). In this study, high correlation coefficients occurred between some a priori 396 CEREAL CHEMISTRY

10 expected pairs of responses; some were not anticipated, however. The temperature profile in the barrel was adjusted to control the extent of heat treatment applied to the dough during processing. The nature of thermo/chemical/mechanical changes occurring in the ingredient mix affects the viscosity of the dough that develops, which thus affects the extrusion processing parameters. Hence, we expected strong correlations between barrel and dough temperature, between die and dough temperature, and between apparent viscosity, torque, and SME. As anticipated, several of these correlation coefficients exhibited very strong relationships, with absolute r values >0.90 (P < 0.01) (Table VII). The independent variables controlled in our experiments will affect the extruder processing conditions, which in turn will affect the extrudate properties. Hence, we expected good correlations between the processing conditions and extrudate properties. As anticipated, mass flow rate and moisture content, WAI, and dough temperature at the die, sinking velocity, and dough temperature at the barrel, apparent viscosity, and die pressure, sinking velocity, and dough temperature at the die, and bulk density and die diameter had correlation coefficients with an absolute value >0.70. It was also anticipated that correlations between extrudate properties such as bulk density, unit density, sinking velocity, and color would occur. As expected, the correlation between bulk density and sinking velocity, unit density, and sinking velocity, L* and a* had correlation coefficients with absolute values >0.70. Additionally, the color of the extrudates exhibited correlation with extrusion processing parameters: mass flow rate and L*, mass flow rate and b*, water-solubility index and L*, die pressure and L* all were significant, with correlation coefficients with absolute values > 0.6. These correlations may have the potential for predicting extrusion processing conditions and extrudate properties and should be further investigated. CONCLUSIONS The goal of this study was to investigate the effect of die nozzle dimensions, barrel temperature profile, and moisture content on DDGS-based extrudate properties and extruder processing parameters. All of these factors had significant effects on extrudate properties such as unit density, bulk density, pellet durability, water absorption index, water solubility index, sinking velocity, and color, and extrusion processing parameters such as the mass flow rate, dough temperature, absolute pressure, specific mechanical energy, torque, and apparent viscosity. Increasing the moisture content from 15 to 25% resulted in decreases of 2.0, 16.0, 16.3, 22.9, 18.5, 32.5, and 63.7%, respectively, in bulk density, water solubility index, sinking velocity, L*, b*, mass flow rate, and absolute pressure, but an 11.6, 16.2, and 7.0% increase, respectively, in pellet durability, water absorption index, and a*. On the other hand, increasing temperature from 100 to 140 C resulted in decreases of 17.0, 5.9, 35.4, 50.6, 28.8, 33.9, and 33.9%, respectively, in unit density, pellet durability, sinking velocity, absolute pressure, specific mechanical energy, torque, and apparent viscosity, but a 49.1 and 16.9% increase, respectively, in dough temperature and water absorption index. It was also determined that, using a linear quadratic model, the L/D ratio of the die, along with moisture content and temperature of the transition and die sections, predicted well most of the extrudate and extrusion properties studied. The aim of this study was to investigate extrusion processing of a 40% DDGS aquaculture feed blend on a laboratory scale, as a precursor to scaling up to commercial equipment. Ultimately, production of these types of feeds on a larger extruder may change the interactions observed with this study, but we have examined a wide range of parameter settings, which will be useful for scale-up purposes. Future studies will examine other levels of DDGS as well. ACKNOWLEDGMENTS We thankfully acknowledge the financial support provided by the Agricultural Experiment Station, South Dakota State University, Brookings, SD, and the North Central Agricultural Research Laboratory, USDA, ARS, Brookings, SD. LITERATURE CITED Alves, R. M. L., Grossmann, M. V. E., and Silva, R. S. S. F Gelling properties of extruded yam (Dioscorea alota) starch. Food Chem. 67: Vol. 84, No. 4,

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